Changes in Fv/Fm in elevated nutrients and heat stress
Ana Palacio
10/29/2018
General project set-up
# Load libraries and sources required to run the script
library(tidyverse)
library(ggthemes)
library(lmerTest)
library(emmeans)
library(multcomp)
library(effects)
# Default ggplot settings
Fill.colour<-scale_colour_manual(values = c("black", "gray70", "gray35"))
ggthe_bw<-theme(plot.background=element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
legend.box.background = element_rect(),
panel.background =element_rect(fill = NA, color = "black")
)+
theme_bw()Data exploration
1. Get the files with all the YII by species
# Acer
YII.Acer<-read.csv("YII_Data/YII_Nutrients_Acer.csv", header = T)
YII.Acer$Fragment<-as.character(YII.Acer$Fragment) # Fragment ID to character
YII.Acer<-subset(YII.Acer, Colony!="F")
YII.Acer<-subset(YII.Acer , Treatment!="Dead")
## Genotype information
MOTE<-read.csv("Genotypes_mote.csv", header = TRUE)
YII.Acer<-merge(YII.Acer, MOTE, by="Colony", all.x=TRUE)
# Ofav
YII.Ofav<-read.csv("YII_Data/YII_Nutrients_Ofav.csv")
YII.Ofav$Colony<-factor(as.character(YII.Ofav$Colony),
levels=c("31","6","20","34")) # D dominance order
YII.Ofav$Genotype<-paste("Ofav", YII.Ofav$Colony, sep = "_")
# Ssid
YII.Ssid<-read.csv("YII_Data/YII_Nutrients_Ssid.csv")
YII.Ssid$Colony<-factor(as.character(YII.Ssid$Colony),
levels=c("30","20","24","28","22","23","27") ) # D dominance order
YII.Ssid$Genotype<-paste("Ssid", YII.Ssid$Colony, sep = "_")
# Pool all species the data
YII.data<-dplyr::bind_rows(list(YII.Acer,YII.Ofav,YII.Ssid))
YII.data<-YII.data[,-1]
summary(YII.data)## Time Date Spp Fragment
## Min. : 0.00 Length:6018 Length:6018 Length:6018
## 1st Qu.: 6.00 Class :character Class :character Class :character
## Median :11.00 Mode :character Mode :character Mode :character
## Mean :11.13
## 3rd Qu.:16.00
## Max. :23.00
## Treatment Replicate YII Sample
## Length:6018 Length:6018 Min. :0.0000 Length:6018
## Class :character Class :character 1st Qu.:0.4420 Class :character
## Mode :character Mode :character Median :0.5030 Mode :character
## Mean :0.4989
## 3rd Qu.:0.5720
## Max. :0.6870
## Genotype
## Length:6018
## Class :character
## Mode :character
##
##
## # Organize data type
YII.data$Date<-as.Date(YII.data$Date, "%Y-%m-%d")
YII.data$Days<-(as.numeric(YII.data$Date) -17485)
YII.data$Spp <- as.factor(YII.data$Spp)
YII.data$Treatment[YII.data$Treatment == "Control"] <- "Ambient"
YII.data$Treatment[YII.data$Treatment == "NP"] <- "N+P"
YII.data$Treatment <- as.factor(YII.data$Treatment)
YII.data$Genotype<-factor(as.character(YII.data$Genotype),
levels=c("Acer_07","Acer_08","Acer_31",
"Acer_48","Acer_50","Acer_62",
"Ofav_31","Ofav_6","Ofav_20","Ofav_34",
"Ssid_30","Ssid_20","Ssid_24",
"Ssid_28","Ssid_22","Ssid_23","Ssid_27")) # D dominance order
YII.data$Fragment <- paste(YII.data$Spp, YII.data$Fragment, sep = "_")
# Check the data
str(YII.data)## 'data.frame': 6018 obs. of 10 variables:
## $ Time : int 3 5 3 2 2 6 11 1 7 2 ...
## $ Date : Date, format: "2017-10-19" "2017-11-16" ...
## $ Spp : Factor w/ 3 levels "A.cer","O.fav",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ Fragment : chr "A.cer_284" "A.cer_180" "A.cer_277" "A.cer_180" ...
## $ Treatment: Factor w/ 3 levels "Ambient","N",..: 1 2 1 2 1 3 1 3 1 1 ...
## $ Replicate: chr "R2" "R2" "R2" "R2" ...
## $ YII : num 0.552 0.607 0.56 0.53 0.533 0.648 0.594 0.479 0.633 0.517 ...
## $ Sample : chr "2017-10-19_284" "2017-11-16_180" "2017-10-19_277" "2017-10-10_180" ...
## $ Genotype : Factor w/ 17 levels "Acer_07","Acer_08",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ Days : num -27 1 -27 -36 -36 8 65 -77 14 -36 ... summary(YII.data)## Time Date Spp Fragment
## Min. : 0.00 Min. :2017-07-26 A.cer:2280 Length:6018
## 1st Qu.: 6.00 1st Qu.:2017-11-29 O.fav:1051 Class :character
## Median :11.00 Median :2018-01-19 S.sid:2687 Mode :character
## Mean :11.13 Mean :2018-01-06
## 3rd Qu.:16.00 3rd Qu.:2018-02-15
## Max. :23.00 Max. :2018-04-20
##
## Treatment Replicate YII Sample
## Ambient:2096 Length:6018 Min. :0.0000 Length:6018
## N :1973 Class :character 1st Qu.:0.4420 Class :character
## N+P :1949 Mode :character Median :0.5030 Mode :character
## Mean :0.4989
## 3rd Qu.:0.5720
## Max. :0.6870
##
## Genotype Days
## Acer_62: 577 Min. :-112.00
## Acer_48: 569 1st Qu.: 14.00
## Acer_07: 462 Median : 65.00
## Ssid_20: 402 Mean : 52.41
## Ssid_23: 402 3rd Qu.: 92.00
## Ssid_30: 400 Max. : 156.00
## (Other):3206 summary(YII.data$Genotype)## Acer_07 Acer_08 Acer_31 Acer_48 Acer_50 Acer_62 Ofav_31 Ofav_6 Ofav_20
## 462 145 304 569 223 577 213 275 284
## Ofav_34 Ssid_30 Ssid_20 Ssid_24 Ssid_28 Ssid_22 Ssid_23 Ssid_27
## 279 400 402 362 332 389 402 400 # Remove baseline values
YII.data<-subset(YII.data, Days>-1)
# Remove recovery values
YII.data<-subset(YII.data, Days<112)
# YII.Wide<- reshape(YII.data, idvar = "Fragment", timevar = "Days", direction = "wide")
# Subset data before heat stress (Only nutrients)
YII.nutrients<-subset(YII.data, Days<80)2. Exploratory graphs
All time points (nutrients + heat stress)
- Colony (Genotype) differences
YII_Colony<- ggplot(YII.data, aes (Days, YII, colour=Genotype)) +
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar", width = 0.5)+
stat_summary(fun.y=mean, geom="line", alpha=0.6) + theme_bw()
YII_Colony + ylim(0.0, 0.65) + facet_grid (Spp~Treatment)
YII_Fragment<- ggplot(YII.data, aes (Days, YII, colour=factor(Fragment))) +
stat_summary(fun.y=mean, geom="line", alpha=0.6) +
theme_bw() + theme(legend.position = "none")
YII_Fragment + ylim(0.0, 0.65) + facet_grid (Spp~Treatment)
YII_Frag_Gen<- ggplot(YII.data, aes (Days, YII, colour=Genotype, shape=Fragment)) +
stat_summary(fun.y=mean, geom="line", alpha=0.5) +
theme_bw() + theme(legend.position = "bottom",
legend.title = element_blank())
YII_Frag_Gen + ylim(0.0, 0.65) + facet_grid (Spp~Treatment)
- Treatment differences
YII_Treat<- ggplot(YII.data, aes (Days, YII, colour=Treatment)) +
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar", width = 0.2, position = position_dodge(1) )+
stat_summary(fun.y=mean, geom="line") + ggthe_bw +
theme(legend.position="bottom",
strip.background = element_rect(fill="white"))+
scale_y_continuous(limits = c(0.2, 0.7),
breaks = seq(0.2, 0.6, 0.1),
expand = c(0, 0),
name=("Fv/Fm")) +
scale_x_continuous(name="Days in the experiment",
limits = c(-1,113),
breaks = seq(0, 113, 15),
expand = c(0, 0))+
annotate("rect", xmin= 2, xmax = 86,
ymin = 0.2, ymax =0.3, fill="blue", alpha = .05)+
annotate("rect", xmin= 72, xmax = 85,
ymin = 0.2, ymax =0.7, fill="orange", alpha = .05)+
annotate("rect", xmin= 85, xmax = 113,
ymin = 0.2, ymax =0.7, fill="red", alpha = .05) + facet_grid (Spp~.)
YII_Treat
Figure 3
YII_Treat_BW<- ggplot(YII.data, aes (Days, YII, colour=factor(Treatment), shape=factor(Treatment))) +
ggthe_bw + Fill.colour+
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar", width = 1, position = position_dodge(1) )+
stat_summary(fun.y=mean, geom="line", position = position_dodge(1), linetype=1, alpha=0.8) +
stat_summary(fun.y=mean, geom="point", size =1,
position=position_dodge(width=1)) +
theme(legend.position="bottom",
legend.title = element_blank(),
strip.background = element_rect(fill="white"))+
scale_y_continuous(limits = c(0.1, 0.7),
breaks = seq(0.1, 0.6, 0.1),
expand = c(0, 0),
name=expression(~italic("Fv / Fm"))) +
scale_x_continuous(name="Days in the experiment",
limits = c(-1,113),
breaks = seq(0, 113, 15),
expand = c(0, 0))+
annotate("segment", x = 2, xend = 91, y = 0.12, yend = 0.13,
colour = "gray90", linetype=2)+
annotate("segment", x = 79, xend = 91, y = 0.12, yend = 0.25,
colour = "gray90", linetype=4)+
annotate("segment", x = 91, xend = 110, y = 0.25, yend = 0.25,
colour = "gray90", linetype=3)
Figure3<-YII_Treat_BW +facet_grid (Spp~.)+
annotate("text", x = 45, y = 0.2, label = "Nutrients", size=3)+
annotate("text", x = 99, y = 0.2, label = "Bleaching", size=3)
Figure3
#ggsave(file="5.3_YII_Treat.svg", plot=YII_Treat, width=4.0, height=6)Figure 3 Supplemantary: Treatment effect by genotype
Figure3b<-YII_Treat_BW +facet_wrap (~Genotype, ncol = 6)
Figure3b
#ggsave(file="5.3_YII_Treat.svg", plot=YII_Treat, width=4.0, height=6)YII GLMs
#Time as a factor, not as int
str(YII.data)## 'data.frame': 5016 obs. of 10 variables:
## $ Time : int 5 6 11 7 11 7 9 7 8 6 ...
## $ Date : Date, format: "2017-11-16" "2017-11-23" ...
## $ Spp : Factor w/ 3 levels "A.cer","O.fav",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ Fragment : chr "A.cer_180" "A.cer_283" "A.cer_290" "A.cer_182" ...
## $ Treatment: Factor w/ 3 levels "Ambient","N",..: 2 3 1 1 3 2 1 2 1 3 ...
## $ Replicate: chr "R2" "R1" "R2" "R1" ...
## $ YII : num 0.607 0.648 0.594 0.633 0.621 0.636 0.63 0.637 0.638 0.637 ...
## $ Sample : chr "2017-11-16_180" "2017-11-23_283" "2018-01-19_290" "2017-11-29_182" ...
## $ Genotype : Factor w/ 17 levels "Acer_07","Acer_08",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ Days : num 1 8 65 14 65 14 28 14 21 8 ... YII.data$DaysF<-as.factor(YII.data$Days)
# All spp together
LME1<-lmer(YII ~ Treatment * DaysF * Spp + (1|Genotype),
REML=TRUE, data=YII.data, na.action=na.omit)
lmerTest::step (LME1)## Backward reduced random-effect table:
##
## Eliminated npar logLik AIC LRT Df Pr(>Chisq)
## <none> 154 8706.6 -17105
## (1 | Genotype) 0 153 8298.0 -16290 817.37 1 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Backward reduced fixed-effect table:
## Degrees of freedom method: Satterthwaite
##
## Eliminated Sum Sq Mean Sq NumDF DenDF F value
## Treatment:DaysF:Spp 0 1.2863 0.020417 63 4850.1 14.076
## Pr(>F)
## Treatment:DaysF:Spp < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Model found:
## YII ~ Treatment * DaysF * Spp + (1 | Genotype) drop1(LME1, test = "Chisq")## Single term deletions using Satterthwaite's method:
##
## Model:
## YII ~ Treatment * DaysF * Spp + (1 | Genotype)
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## Treatment:DaysF:Spp 1.2863 0.020417 63 4850.1 14.076 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 summary(LME1)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: YII ~ Treatment * DaysF * Spp + (1 | Genotype)
## Data: YII.data
##
## REML criterion at convergence: -17413.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -9.6697 -0.4535 0.0540 0.5460 3.4938
##
## Random effects:
## Groups Name Variance Std.Dev.
## Genotype (Intercept) 0.0003385 0.01840
## Residual 0.0014505 0.03808
## Number of obs: 5016, groups: Genotype, 17
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 6.122e-01 9.690e-03 3.756e+01 63.171
## TreatmentN -1.124e-02 8.520e-03 4.850e+03 -1.320
## TreatmentN+P -6.996e-03 8.572e-03 4.850e+03 -0.816
## DaysF8 -1.641e-03 8.625e-03 4.850e+03 -0.190
## DaysF14 6.462e-03 8.625e-03 4.850e+03 0.749
## DaysF21 -6.231e-03 8.625e-03 4.850e+03 -0.722
## DaysF28 -1.144e-02 8.625e-03 4.850e+03 -1.326
## DaysF49 -3.321e-02 8.625e-03 4.850e+03 -3.850
## DaysF65 -4.377e-02 8.625e-03 4.850e+03 -5.075
## DaysF71 -4.256e-02 8.625e-03 4.850e+03 -4.935
## DaysF76 -5.182e-02 8.625e-03 4.850e+03 -6.009
## DaysF84 -4.619e-02 9.084e-03 4.850e+03 -5.084
## DaysF89 -6.447e-02 9.084e-03 4.850e+03 -7.097
## DaysF92 -5.344e-02 9.084e-03 4.850e+03 -5.882
## DaysF96 -5.322e-02 9.084e-03 4.850e+03 -5.858
## DaysF99 -7.894e-02 9.084e-03 4.850e+03 -8.689
## DaysF103 -9.828e-02 9.084e-03 4.850e+03 -10.819
## DaysF106 -1.152e-01 9.084e-03 4.850e+03 -12.680
## DaysF110 -2.124e-01 9.084e-03 4.850e+03 -23.381
## SppO.fav -1.057e-01 1.546e-02 3.892e+01 -6.840
## SppS.sid -1.454e-01 1.300e-02 3.534e+01 -11.182
## TreatmentN:DaysF8 2.749e-02 1.205e-02 4.850e+03 2.282
## TreatmentN+P:DaysF8 2.182e-02 1.212e-02 4.850e+03 1.800
## TreatmentN:DaysF14 8.197e-03 1.205e-02 4.850e+03 0.680
## TreatmentN+P:DaysF14 1.586e-02 1.212e-02 4.850e+03 1.309
## TreatmentN:DaysF21 4.433e-02 1.205e-02 4.850e+03 3.680
## TreatmentN+P:DaysF21 2.751e-02 1.212e-02 4.850e+03 2.269
## TreatmentN:DaysF28 4.173e-02 1.205e-02 4.850e+03 3.464
## TreatmentN+P:DaysF28 4.296e-02 1.212e-02 4.850e+03 3.544
## TreatmentN:DaysF49 6.755e-02 1.205e-02 4.850e+03 5.607
## TreatmentN+P:DaysF49 6.271e-02 1.212e-02 4.850e+03 5.173
## TreatmentN:DaysF65 4.211e-02 1.205e-02 4.850e+03 3.495
## TreatmentN+P:DaysF65 5.670e-02 1.216e-02 4.850e+03 4.663
## TreatmentN:DaysF71 5.384e-02 1.216e-02 4.850e+03 4.426
## TreatmentN+P:DaysF71 2.865e-02 1.216e-02 4.850e+03 2.356
## TreatmentN:DaysF76 5.275e-02 1.221e-02 4.850e+03 4.321
## TreatmentN+P:DaysF76 3.944e-02 1.216e-02 4.850e+03 3.244
## TreatmentN:DaysF84 3.662e-02 1.303e-02 4.850e+03 2.811
## TreatmentN+P:DaysF84 4.123e-02 1.293e-02 4.850e+03 3.189
## TreatmentN:DaysF89 3.895e-02 1.310e-02 4.850e+03 2.972
## TreatmentN+P:DaysF89 3.061e-02 1.293e-02 4.850e+03 2.368
## TreatmentN:DaysF92 -4.387e-03 1.346e-02 4.850e+03 -0.326
## TreatmentN+P:DaysF92 2.373e-02 1.314e-02 4.850e+03 1.806
## TreatmentN:DaysF96 -4.963e-02 1.396e-02 4.851e+03 -3.555
## TreatmentN+P:DaysF96 -1.925e-02 1.399e-02 4.850e+03 -1.377
## TreatmentN:DaysF99 -1.179e-01 1.428e-02 4.851e+03 -8.257
## TreatmentN+P:DaysF99 -4.192e-02 1.431e-02 4.851e+03 -2.929
## TreatmentN:DaysF103 -1.128e-01 1.492e-02 4.851e+03 -7.558
## TreatmentN+P:DaysF103 -9.829e-02 1.450e-02 4.851e+03 -6.779
## TreatmentN:DaysF106 -1.806e-01 1.674e-02 4.851e+03 -10.790
## TreatmentN+P:DaysF106 -1.439e-01 1.551e-02 4.851e+03 -9.277
## TreatmentN:DaysF110 6.492e-02 1.122e-02 4.850e+03 5.789
## TreatmentN+P:DaysF110 -1.302e-01 2.024e-02 4.850e+03 -6.435
## TreatmentN:SppO.fav 1.945e-02 1.391e-02 4.850e+03 1.399
## TreatmentN+P:SppO.fav 1.870e-02 1.394e-02 4.850e+03 1.342
## TreatmentN:SppS.sid -1.402e-02 1.122e-02 4.850e+03 -1.250
## TreatmentN+P:SppS.sid -4.073e-04 1.130e-02 4.850e+03 -0.036
## DaysF8:SppO.fav -1.219e-02 1.397e-02 4.850e+03 -0.873
## DaysF14:SppO.fav 3.050e-02 1.397e-02 4.850e+03 2.182
## DaysF21:SppO.fav -2.289e-02 1.397e-02 4.850e+03 -1.638
## DaysF28:SppO.fav -2.314e-03 1.397e-02 4.850e+03 -0.166
## DaysF49:SppO.fav -1.959e-02 1.397e-02 4.850e+03 -1.402
## DaysF65:SppO.fav 3.827e-02 1.397e-02 4.850e+03 2.739
## DaysF71:SppO.fav 3.856e-03 1.397e-02 4.850e+03 0.276
## DaysF76:SppO.fav 1.278e-02 1.397e-02 4.850e+03 0.915
## DaysF84:SppO.fav 3.108e-02 1.528e-02 4.850e+03 2.034
## DaysF89:SppO.fav 3.480e-02 1.528e-02 4.850e+03 2.277
## DaysF92:SppO.fav 6.172e-02 1.548e-02 4.850e+03 3.987
## DaysF96:SppO.fav -2.083e-02 1.548e-02 4.850e+03 -1.345
## DaysF99:SppO.fav 3.557e-03 1.548e-02 4.850e+03 0.230
## DaysF103:SppO.fav 2.501e-03 1.548e-02 4.850e+03 0.162
## DaysF106:SppO.fav -1.458e-02 1.571e-02 4.850e+03 -0.928
## DaysF110:SppO.fav 1.197e-01 1.626e-02 4.850e+03 7.360
## DaysF8:SppS.sid 2.929e-02 1.132e-02 4.850e+03 2.588
## DaysF14:SppS.sid 7.778e-02 1.132e-02 4.850e+03 6.872
## DaysF21:SppS.sid 2.895e-02 1.132e-02 4.850e+03 2.558
## DaysF28:SppS.sid 7.507e-02 1.132e-02 4.850e+03 6.632
## DaysF49:SppS.sid 5.378e-02 1.132e-02 4.850e+03 4.752
## DaysF65:SppS.sid 6.916e-02 1.134e-02 4.850e+03 6.099
## DaysF71:SppS.sid 5.727e-02 1.134e-02 4.850e+03 5.050
## DaysF76:SppS.sid 6.734e-02 1.134e-02 4.850e+03 5.938
## DaysF84:SppS.sid 4.841e-02 1.211e-02 4.850e+03 3.999
## DaysF89:SppS.sid 3.723e-02 1.211e-02 4.850e+03 3.075
## DaysF92:SppS.sid 3.507e-02 1.211e-02 4.850e+03 2.897
## DaysF96:SppS.sid -3.794e-02 1.211e-02 4.850e+03 -3.134
## DaysF99:SppS.sid -1.238e-02 1.211e-02 4.850e+03 -1.022
## DaysF103:SppS.sid -1.519e-02 1.211e-02 4.850e+03 -1.254
## DaysF106:SppS.sid -9.407e-03 1.211e-02 4.850e+03 -0.777
## DaysF110:SppS.sid 1.168e-01 1.211e-02 4.850e+03 9.648
## TreatmentN:DaysF8:SppO.fav -2.412e-02 1.967e-02 4.850e+03 -1.226
## TreatmentN+P:DaysF8:SppO.fav -2.623e-02 1.971e-02 4.850e+03 -1.331
## TreatmentN:DaysF14:SppO.fav -2.474e-02 1.967e-02 4.850e+03 -1.258
## TreatmentN+P:DaysF14:SppO.fav -2.141e-02 1.971e-02 4.850e+03 -1.086
## TreatmentN:DaysF21:SppO.fav -4.079e-02 1.967e-02 4.850e+03 -2.074
## TreatmentN+P:DaysF21:SppO.fav -2.167e-02 1.971e-02 4.850e+03 -1.099
## TreatmentN:DaysF28:SppO.fav -2.273e-02 1.967e-02 4.850e+03 -1.156
## TreatmentN+P:DaysF28:SppO.fav -9.669e-03 1.971e-02 4.850e+03 -0.490
## TreatmentN:DaysF49:SppO.fav -3.638e-02 1.967e-02 4.850e+03 -1.850
## TreatmentN+P:DaysF49:SppO.fav -2.404e-02 1.971e-02 4.850e+03 -1.219
## TreatmentN:DaysF65:SppO.fav -7.082e-02 1.967e-02 4.850e+03 -3.600
## TreatmentN+P:DaysF65:SppO.fav -5.528e-02 1.974e-02 4.850e+03 -2.801
## TreatmentN:DaysF71:SppO.fav -5.492e-02 1.974e-02 4.850e+03 -2.782
## TreatmentN+P:DaysF71:SppO.fav -6.173e-02 1.974e-02 4.850e+03 -3.127
## TreatmentN:DaysF76:SppO.fav -5.546e-02 1.977e-02 4.850e+03 -2.806
## TreatmentN+P:DaysF76:SppO.fav -4.890e-02 1.974e-02 4.850e+03 -2.477
## TreatmentN:DaysF84:SppO.fav -4.521e-02 2.172e-02 4.850e+03 -2.081
## TreatmentN+P:DaysF84:SppO.fav -4.250e-02 2.166e-02 4.850e+03 -1.962
## TreatmentN:DaysF89:SppO.fav -6.400e-02 2.191e-02 4.850e+03 -2.921
## TreatmentN+P:DaysF89:SppO.fav -3.270e-02 2.166e-02 4.850e+03 -1.509
## TreatmentN:DaysF92:SppO.fav -2.266e-02 2.242e-02 4.850e+03 -1.011
## TreatmentN+P:DaysF92:SppO.fav -5.863e-02 2.206e-02 4.850e+03 -2.657
## TreatmentN:DaysF96:SppO.fav 4.542e-02 2.272e-02 4.850e+03 1.999
## TreatmentN+P:DaysF96:SppO.fav 2.297e-02 2.273e-02 4.850e+03 1.010
## TreatmentN:DaysF99:SppO.fav 8.656e-02 2.292e-02 4.850e+03 3.777
## TreatmentN+P:DaysF99:SppO.fav 3.442e-02 2.355e-02 4.850e+03 1.461
## TreatmentN:DaysF103:SppO.fav 8.987e-02 2.332e-02 4.850e+03 3.854
## TreatmentN+P:DaysF103:SppO.fav 1.016e-01 2.367e-02 4.850e+03 4.291
## TreatmentN:DaysF106:SppO.fav 1.431e-01 2.483e-02 4.850e+03 5.765
## TreatmentN+P:DaysF106:SppO.fav 1.174e-01 2.444e-02 4.850e+03 4.805
## TreatmentN:DaysF110:SppO.fav -1.363e-01 2.210e-02 4.850e+03 -6.167
## TreatmentN+P:DaysF110:SppO.fav 9.427e-02 2.799e-02 4.850e+03 3.368
## TreatmentN:DaysF8:SppS.sid 1.403e-03 1.586e-02 4.850e+03 0.088
## TreatmentN+P:DaysF8:SppS.sid 1.772e-02 1.598e-02 4.850e+03 1.109
## TreatmentN:DaysF14:SppS.sid 1.325e-02 1.586e-02 4.850e+03 0.836
## TreatmentN+P:DaysF14:SppS.sid -4.293e-03 1.598e-02 4.850e+03 -0.269
## TreatmentN:DaysF21:SppS.sid -2.832e-03 1.586e-02 4.850e+03 -0.179
## TreatmentN+P:DaysF21:SppS.sid 1.396e-02 1.598e-02 4.850e+03 0.874
## TreatmentN:DaysF28:SppS.sid 4.460e-03 1.586e-02 4.850e+03 0.281
## TreatmentN+P:DaysF28:SppS.sid -1.716e-02 1.598e-02 4.850e+03 -1.074
## TreatmentN:DaysF49:SppS.sid -4.065e-02 1.586e-02 4.850e+03 -2.563
## TreatmentN+P:DaysF49:SppS.sid -5.656e-02 1.598e-02 4.850e+03 -3.540
## TreatmentN:DaysF65:SppS.sid -6.296e-02 1.588e-02 4.850e+03 -3.965
## TreatmentN+P:DaysF65:SppS.sid -5.925e-02 1.604e-02 4.850e+03 -3.694
## TreatmentN:DaysF71:SppS.sid -4.964e-02 1.597e-02 4.850e+03 -3.109
## TreatmentN+P:DaysF71:SppS.sid -2.798e-02 1.603e-02 4.850e+03 -1.746
## TreatmentN:DaysF76:SppS.sid -4.729e-02 1.600e-02 4.850e+03 -2.956
## TreatmentN+P:DaysF76:SppS.sid -4.181e-02 1.603e-02 4.850e+03 -2.609
## TreatmentN:DaysF84:SppS.sid -4.825e-02 1.719e-02 4.850e+03 -2.806
## TreatmentN+P:DaysF84:SppS.sid -3.355e-02 1.717e-02 4.850e+03 -1.954
## TreatmentN:DaysF89:SppS.sid -2.767e-02 1.725e-02 4.850e+03 -1.604
## TreatmentN+P:DaysF89:SppS.sid -3.895e-02 1.717e-02 4.850e+03 -2.268
## TreatmentN:DaysF92:SppS.sid 3.091e-02 1.752e-02 4.850e+03 1.764
## TreatmentN+P:DaysF92:SppS.sid -1.743e-02 1.733e-02 4.850e+03 -1.006
## TreatmentN:DaysF96:SppS.sid 1.169e-01 1.791e-02 4.850e+03 6.529
## TreatmentN+P:DaysF96:SppS.sid 4.420e-02 1.798e-02 4.850e+03 2.458
## TreatmentN:DaysF99:SppS.sid 1.772e-01 1.816e-02 4.850e+03 9.758
## TreatmentN+P:DaysF99:SppS.sid 5.259e-02 1.824e-02 4.850e+03 2.884
## TreatmentN:DaysF103:SppS.sid 1.909e-01 1.867e-02 4.851e+03 10.229
## TreatmentN+P:DaysF103:SppS.sid 1.203e-01 1.838e-02 4.850e+03 6.542
## TreatmentN:DaysF106:SppS.sid 2.355e-01 2.015e-02 4.850e+03 11.686
## TreatmentN+P:DaysF106:SppS.sid 1.514e-01 1.919e-02 4.850e+03 7.892
## TreatmentN+P:DaysF110:SppS.sid 1.491e-01 2.318e-02 4.850e+03 6.431
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## TreatmentN 0.186973
## TreatmentN+P 0.414421
## DaysF8 0.849102
## DaysF14 0.453770
## DaysF21 0.470054
## DaysF28 0.184911
## DaysF49 0.000120 ***
## DaysF65 4.02e-07 ***
## DaysF71 8.27e-07 ***
## DaysF76 2.01e-09 ***
## DaysF84 3.83e-07 ***
## DaysF89 1.46e-12 ***
## DaysF92 4.32e-09 ***
## DaysF96 4.99e-09 ***
## DaysF99 < 2e-16 ***
## DaysF103 < 2e-16 ***
## DaysF106 < 2e-16 ***
## DaysF110 < 2e-16 ***
## SppO.fav 3.59e-08 ***
## SppS.sid 3.71e-13 ***
## TreatmentN:DaysF8 0.022519 *
## TreatmentN+P:DaysF8 0.071933 .
## TreatmentN:DaysF14 0.496282
## TreatmentN+P:DaysF14 0.190659
## TreatmentN:DaysF21 0.000236 ***
## TreatmentN+P:DaysF21 0.023290 *
## TreatmentN:DaysF28 0.000537 ***
## TreatmentN+P:DaysF28 0.000397 ***
## TreatmentN:DaysF49 2.18e-08 ***
## TreatmentN+P:DaysF49 2.39e-07 ***
## TreatmentN:DaysF65 0.000477 ***
## TreatmentN+P:DaysF65 3.20e-06 ***
## TreatmentN:DaysF71 9.79e-06 ***
## TreatmentN+P:DaysF71 0.018517 *
## TreatmentN:DaysF76 1.58e-05 ***
## TreatmentN+P:DaysF76 0.001188 **
## TreatmentN:DaysF84 0.004964 **
## TreatmentN+P:DaysF84 0.001435 **
## TreatmentN:DaysF89 0.002972 **
## TreatmentN+P:DaysF89 0.017926 *
## TreatmentN:DaysF92 0.744578
## TreatmentN+P:DaysF92 0.070946 .
## TreatmentN:DaysF96 0.000382 ***
## TreatmentN+P:DaysF96 0.168662
## TreatmentN:DaysF99 < 2e-16 ***
## TreatmentN+P:DaysF99 0.003420 **
## TreatmentN:DaysF103 4.85e-14 ***
## TreatmentN+P:DaysF103 1.36e-11 ***
## TreatmentN:DaysF106 < 2e-16 ***
## TreatmentN+P:DaysF106 < 2e-16 ***
## TreatmentN:DaysF110 7.55e-09 ***
## TreatmentN+P:DaysF110 1.36e-10 ***
## TreatmentN:SppO.fav 0.162010
## TreatmentN+P:SppO.fav 0.179750
## TreatmentN:SppS.sid 0.211509
## TreatmentN+P:SppS.sid 0.971249
## DaysF8:SppO.fav 0.382957
## DaysF14:SppO.fav 0.029121 *
## DaysF21:SppO.fav 0.101399
## DaysF28:SppO.fav 0.868472
## DaysF49:SppO.fav 0.161067
## DaysF65:SppO.fav 0.006190 **
## DaysF71:SppO.fav 0.782608
## DaysF76:SppO.fav 0.360491
## DaysF84:SppO.fav 0.042049 *
## DaysF89:SppO.fav 0.022837 *
## DaysF92:SppO.fav 6.79e-05 ***
## DaysF96:SppO.fav 0.178566
## DaysF99:SppO.fav 0.818305
## DaysF103:SppO.fav 0.871697
## DaysF106:SppO.fav 0.353303
## DaysF110:SppO.fav 2.15e-13 ***
## DaysF8:SppS.sid 0.009689 **
## DaysF14:SppS.sid 7.13e-12 ***
## DaysF21:SppS.sid 0.010555 *
## DaysF28:SppS.sid 3.67e-11 ***
## DaysF49:SppS.sid 2.08e-06 ***
## DaysF65:SppS.sid 1.15e-09 ***
## DaysF71:SppS.sid 4.57e-07 ***
## DaysF76:SppS.sid 3.09e-09 ***
## DaysF84:SppS.sid 6.46e-05 ***
## DaysF89:SppS.sid 0.002115 **
## DaysF92:SppS.sid 0.003785 **
## DaysF96:SppS.sid 0.001736 **
## DaysF99:SppS.sid 0.306757
## DaysF103:SppS.sid 0.209807
## DaysF106:SppS.sid 0.437188
## DaysF110:SppS.sid < 2e-16 ***
## TreatmentN:DaysF8:SppO.fav 0.220160
## TreatmentN+P:DaysF8:SppO.fav 0.183367
## TreatmentN:DaysF14:SppO.fav 0.208549
## TreatmentN+P:DaysF14:SppO.fav 0.277633
## TreatmentN:DaysF21:SppO.fav 0.038167 *
## TreatmentN+P:DaysF21:SppO.fav 0.271678
## TreatmentN:DaysF28:SppO.fav 0.247927
## TreatmentN+P:DaysF28:SppO.fav 0.623823
## TreatmentN:DaysF49:SppO.fav 0.064435 .
## TreatmentN+P:DaysF49:SppO.fav 0.222771
## TreatmentN:DaysF65:SppO.fav 0.000321 ***
## TreatmentN+P:DaysF65:SppO.fav 0.005119 **
## TreatmentN:DaysF71:SppO.fav 0.005418 **
## TreatmentN+P:DaysF71:SppO.fav 0.001774 **
## TreatmentN:DaysF76:SppO.fav 0.005042 **
## TreatmentN+P:DaysF76:SppO.fav 0.013268 *
## TreatmentN:DaysF84:SppO.fav 0.037498 *
## TreatmentN+P:DaysF84:SppO.fav 0.049823 *
## TreatmentN:DaysF89:SppO.fav 0.003501 **
## TreatmentN+P:DaysF89:SppO.fav 0.131282
## TreatmentN:DaysF92:SppO.fav 0.312131
## TreatmentN+P:DaysF92:SppO.fav 0.007899 **
## TreatmentN:DaysF96:SppO.fav 0.045632 *
## TreatmentN+P:DaysF96:SppO.fav 0.312365
## TreatmentN:DaysF99:SppO.fav 0.000161 ***
## TreatmentN+P:DaysF99:SppO.fav 0.143965
## TreatmentN:DaysF103:SppO.fav 0.000118 ***
## TreatmentN+P:DaysF103:SppO.fav 1.81e-05 ***
## TreatmentN:DaysF106:SppO.fav 8.67e-09 ***
## TreatmentN+P:DaysF106:SppO.fav 1.59e-06 ***
## TreatmentN:DaysF110:SppO.fav 7.51e-10 ***
## TreatmentN+P:DaysF110:SppO.fav 0.000762 ***
## TreatmentN:DaysF8:SppS.sid 0.929541
## TreatmentN+P:DaysF8:SppS.sid 0.267413
## TreatmentN:DaysF14:SppS.sid 0.403459
## TreatmentN+P:DaysF14:SppS.sid 0.788218
## TreatmentN:DaysF21:SppS.sid 0.858288
## TreatmentN+P:DaysF21:SppS.sid 0.382361
## TreatmentN:DaysF28:SppS.sid 0.778589
## TreatmentN+P:DaysF28:SppS.sid 0.283043
## TreatmentN:DaysF49:SppS.sid 0.010419 *
## TreatmentN+P:DaysF49:SppS.sid 0.000405 ***
## TreatmentN:DaysF65:SppS.sid 7.44e-05 ***
## TreatmentN+P:DaysF65:SppS.sid 0.000223 ***
## TreatmentN:DaysF71:SppS.sid 0.001887 **
## TreatmentN+P:DaysF71:SppS.sid 0.080894 .
## TreatmentN:DaysF76:SppS.sid 0.003134 **
## TreatmentN+P:DaysF76:SppS.sid 0.009107 **
## TreatmentN:DaysF84:SppS.sid 0.005029 **
## TreatmentN+P:DaysF84:SppS.sid 0.050764 .
## TreatmentN:DaysF89:SppS.sid 0.108706
## TreatmentN+P:DaysF89:SppS.sid 0.023365 *
## TreatmentN:DaysF92:SppS.sid 0.077815 .
## TreatmentN+P:DaysF92:SppS.sid 0.314545
## TreatmentN:DaysF96:SppS.sid 7.30e-11 ***
## TreatmentN+P:DaysF96:SppS.sid 0.014002 *
## TreatmentN:DaysF99:SppS.sid < 2e-16 ***
## TreatmentN+P:DaysF99:SppS.sid 0.003946 **
## TreatmentN:DaysF103:SppS.sid < 2e-16 ***
## TreatmentN+P:DaysF103:SppS.sid 6.69e-11 ***
## TreatmentN:DaysF106:SppS.sid < 2e-16 ***
## TreatmentN+P:DaysF106:SppS.sid 3.65e-15 ***
## TreatmentN+P:DaysF110:SppS.sid 1.39e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## fixed-effect model matrix is rank deficient so dropping 1 column / coefficient # plot(Effect(c("Treatment","Spp","DaysF"), LME1), x.var="DaysF", multiline=T, ci.style="bars",
# ylab="Fv/Fm", xlab="Days in nutient treatments")
# EMMs
All.YII.emm<-emmeans(LME1, ~Treatment * DaysF* Spp)
emmip(LME1, ~DaysF|Treatment|Spp, CIs = TRUE) + theme_bw() + facet_grid(Spp~Treatment)
# Spp responded differently, do separate analysis for each oneA.cer model
LME_Acer<-lmerTest::lmer(YII ~ Treatment * DaysF + (1|Genotype/Fragment),
data=subset(YII.data, Spp=="A.cer"), na.action=na.omit)
summary(LME_Acer)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: YII ~ Treatment * DaysF + (1 | Genotype/Fragment)
## Data: subset(YII.data, Spp == "A.cer")
##
## REML criterion at convergence: -7076.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -14.5929 -0.4042 0.0553 0.4562 5.6395
##
## Random effects:
## Groups Name Variance Std.Dev.
## Fragment:Genotype (Intercept) 0.0001250 0.01118
## Genotype (Intercept) 0.0001976 0.01406
## Residual 0.0005142 0.02268
## Number of obs: 1619, groups: Fragment:Genotype, 120; Genotype, 6
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.118e-01 7.053e-03 1.053e+01 86.741 2.23e-16
## TreatmentN -1.124e-02 5.657e-03 1.015e+03 -1.986 0.047290
## TreatmentN+P -6.843e-03 5.692e-03 1.014e+03 -1.202 0.229520
## DaysF8 -1.641e-03 5.135e-03 1.449e+03 -0.320 0.749330
## DaysF14 6.462e-03 5.135e-03 1.449e+03 1.258 0.208464
## DaysF21 -6.231e-03 5.135e-03 1.449e+03 -1.213 0.225167
## DaysF28 -1.144e-02 5.135e-03 1.449e+03 -2.227 0.026094
## DaysF49 -3.320e-02 5.135e-03 1.449e+03 -6.467 1.37e-10
## DaysF65 -4.377e-02 5.135e-03 1.449e+03 -8.524 < 2e-16
## DaysF71 -4.256e-02 5.135e-03 1.449e+03 -8.289 2.57e-16
## DaysF76 -5.182e-02 5.135e-03 1.449e+03 -10.092 < 2e-16
## DaysF84 -4.601e-02 5.429e-03 1.458e+03 -8.475 < 2e-16
## DaysF89 -6.429e-02 5.429e-03 1.458e+03 -11.843 < 2e-16
## DaysF92 -5.326e-02 5.429e-03 1.458e+03 -9.811 < 2e-16
## DaysF96 -5.304e-02 5.429e-03 1.458e+03 -9.771 < 2e-16
## DaysF99 -7.876e-02 5.429e-03 1.458e+03 -14.508 < 2e-16
## DaysF103 -9.810e-02 5.429e-03 1.458e+03 -18.071 < 2e-16
## DaysF106 -1.150e-01 5.429e-03 1.458e+03 -21.185 < 2e-16
## DaysF110 -2.122e-01 5.429e-03 1.458e+03 -39.093 < 2e-16
## TreatmentN:DaysF8 2.749e-02 7.173e-03 1.449e+03 3.833 0.000132
## TreatmentN+P:DaysF8 2.182e-02 7.216e-03 1.449e+03 3.023 0.002545
## TreatmentN:DaysF14 8.197e-03 7.173e-03 1.449e+03 1.143 0.253309
## TreatmentN+P:DaysF14 1.586e-02 7.216e-03 1.449e+03 2.198 0.028086
## TreatmentN:DaysF21 4.433e-02 7.173e-03 1.449e+03 6.180 8.31e-10
## TreatmentN+P:DaysF21 2.751e-02 7.216e-03 1.449e+03 3.812 0.000144
## TreatmentN:DaysF28 4.173e-02 7.173e-03 1.449e+03 5.818 7.33e-09
## TreatmentN+P:DaysF28 4.296e-02 7.216e-03 1.449e+03 5.953 3.29e-09
## TreatmentN:DaysF49 6.755e-02 7.173e-03 1.449e+03 9.417 < 2e-16
## TreatmentN+P:DaysF49 6.270e-02 7.216e-03 1.449e+03 8.689 < 2e-16
## TreatmentN:DaysF65 4.211e-02 7.173e-03 1.449e+03 5.871 5.36e-09
## TreatmentN+P:DaysF65 5.627e-02 7.241e-03 1.450e+03 7.770 1.47e-14
## TreatmentN:DaysF71 5.273e-02 7.248e-03 1.452e+03 7.276 5.63e-13
## TreatmentN+P:DaysF71 2.822e-02 7.241e-03 1.450e+03 3.897 0.000102
## TreatmentN:DaysF76 5.123e-02 7.275e-03 1.452e+03 7.041 2.93e-12
## TreatmentN+P:DaysF76 3.901e-02 7.241e-03 1.450e+03 5.387 8.33e-08
## TreatmentN:DaysF84 3.559e-02 7.801e-03 1.463e+03 4.562 5.48e-06
## TreatmentN+P:DaysF84 4.129e-02 7.733e-03 1.461e+03 5.339 1.08e-07
## TreatmentN:DaysF89 3.837e-02 7.847e-03 1.463e+03 4.890 1.12e-06
## TreatmentN+P:DaysF89 3.067e-02 7.733e-03 1.461e+03 3.966 7.67e-05
## TreatmentN:DaysF92 -5.437e-03 8.071e-03 1.465e+03 -0.674 0.500593
## TreatmentN+P:DaysF92 2.446e-02 7.863e-03 1.462e+03 3.110 0.001905
## TreatmentN:DaysF96 -4.797e-02 8.377e-03 1.467e+03 -5.727 1.24e-08
## TreatmentN+P:DaysF96 -1.997e-02 8.390e-03 1.466e+03 -2.380 0.017438
## TreatmentN:DaysF99 -1.156e-01 8.576e-03 1.468e+03 -13.482 < 2e-16
## TreatmentN+P:DaysF99 -4.191e-02 8.590e-03 1.467e+03 -4.879 1.18e-06
## TreatmentN:DaysF103 -1.112e-01 8.968e-03 1.469e+03 -12.400 < 2e-16
## TreatmentN+P:DaysF103 -9.820e-02 8.705e-03 1.467e+03 -11.280 < 2e-16
## TreatmentN:DaysF106 -1.810e-01 1.009e-02 1.473e+03 -17.929 < 2e-16
## TreatmentN+P:DaysF106 -1.426e-01 9.331e-03 1.470e+03 -15.285 < 2e-16
## TreatmentN+P:DaysF110 -1.302e-01 1.225e-02 1.476e+03 -10.630 < 2e-16
##
## (Intercept) ***
## TreatmentN *
## TreatmentN+P
## DaysF8
## DaysF14
## DaysF21
## DaysF28 *
## DaysF49 ***
## DaysF65 ***
## DaysF71 ***
## DaysF76 ***
## DaysF84 ***
## DaysF89 ***
## DaysF92 ***
## DaysF96 ***
## DaysF99 ***
## DaysF103 ***
## DaysF106 ***
## DaysF110 ***
## TreatmentN:DaysF8 ***
## TreatmentN+P:DaysF8 **
## TreatmentN:DaysF14
## TreatmentN+P:DaysF14 *
## TreatmentN:DaysF21 ***
## TreatmentN+P:DaysF21 ***
## TreatmentN:DaysF28 ***
## TreatmentN+P:DaysF28 ***
## TreatmentN:DaysF49 ***
## TreatmentN+P:DaysF49 ***
## TreatmentN:DaysF65 ***
## TreatmentN+P:DaysF65 ***
## TreatmentN:DaysF71 ***
## TreatmentN+P:DaysF71 ***
## TreatmentN:DaysF76 ***
## TreatmentN+P:DaysF76 ***
## TreatmentN:DaysF84 ***
## TreatmentN+P:DaysF84 ***
## TreatmentN:DaysF89 ***
## TreatmentN+P:DaysF89 ***
## TreatmentN:DaysF92
## TreatmentN+P:DaysF92 **
## TreatmentN:DaysF96 ***
## TreatmentN+P:DaysF96 *
## TreatmentN:DaysF99 ***
## TreatmentN+P:DaysF99 ***
## TreatmentN:DaysF103 ***
## TreatmentN+P:DaysF103 ***
## TreatmentN:DaysF106 ***
## TreatmentN+P:DaysF106 ***
## TreatmentN+P:DaysF110 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## fixed-effect model matrix is rank deficient so dropping 1 column / coefficient Step.LME_Acer<-step (LME_Acer)
final_fm <- get_model(Step.LME_Acer)
summary(final_fm)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: YII ~ Treatment * DaysF + (1 | Genotype/Fragment)
## Data: subset(YII.data, Spp == "A.cer")
##
## REML criterion at convergence: -7076.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -14.5929 -0.4042 0.0553 0.4562 5.6395
##
## Random effects:
## Groups Name Variance Std.Dev.
## Fragment:Genotype (Intercept) 0.0001250 0.01118
## Genotype (Intercept) 0.0001976 0.01406
## Residual 0.0005142 0.02268
## Number of obs: 1619, groups: Fragment:Genotype, 120; Genotype, 6
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 6.118e-01 7.053e-03 1.053e+01 86.741 2.23e-16
## TreatmentN -1.124e-02 5.657e-03 1.015e+03 -1.986 0.047290
## TreatmentN+P -6.843e-03 5.692e-03 1.014e+03 -1.202 0.229520
## DaysF8 -1.641e-03 5.135e-03 1.449e+03 -0.320 0.749330
## DaysF14 6.462e-03 5.135e-03 1.449e+03 1.258 0.208464
## DaysF21 -6.231e-03 5.135e-03 1.449e+03 -1.213 0.225167
## DaysF28 -1.144e-02 5.135e-03 1.449e+03 -2.227 0.026094
## DaysF49 -3.320e-02 5.135e-03 1.449e+03 -6.467 1.37e-10
## DaysF65 -4.377e-02 5.135e-03 1.449e+03 -8.524 < 2e-16
## DaysF71 -4.256e-02 5.135e-03 1.449e+03 -8.289 2.57e-16
## DaysF76 -5.182e-02 5.135e-03 1.449e+03 -10.092 < 2e-16
## DaysF84 -4.601e-02 5.429e-03 1.458e+03 -8.475 < 2e-16
## DaysF89 -6.429e-02 5.429e-03 1.458e+03 -11.843 < 2e-16
## DaysF92 -5.326e-02 5.429e-03 1.458e+03 -9.811 < 2e-16
## DaysF96 -5.304e-02 5.429e-03 1.458e+03 -9.771 < 2e-16
## DaysF99 -7.876e-02 5.429e-03 1.458e+03 -14.508 < 2e-16
## DaysF103 -9.810e-02 5.429e-03 1.458e+03 -18.071 < 2e-16
## DaysF106 -1.150e-01 5.429e-03 1.458e+03 -21.185 < 2e-16
## DaysF110 -2.122e-01 5.429e-03 1.458e+03 -39.093 < 2e-16
## TreatmentN:DaysF8 2.749e-02 7.173e-03 1.449e+03 3.833 0.000132
## TreatmentN+P:DaysF8 2.182e-02 7.216e-03 1.449e+03 3.023 0.002545
## TreatmentN:DaysF14 8.197e-03 7.173e-03 1.449e+03 1.143 0.253309
## TreatmentN+P:DaysF14 1.586e-02 7.216e-03 1.449e+03 2.198 0.028086
## TreatmentN:DaysF21 4.433e-02 7.173e-03 1.449e+03 6.180 8.31e-10
## TreatmentN+P:DaysF21 2.751e-02 7.216e-03 1.449e+03 3.812 0.000144
## TreatmentN:DaysF28 4.173e-02 7.173e-03 1.449e+03 5.818 7.33e-09
## TreatmentN+P:DaysF28 4.296e-02 7.216e-03 1.449e+03 5.953 3.29e-09
## TreatmentN:DaysF49 6.755e-02 7.173e-03 1.449e+03 9.417 < 2e-16
## TreatmentN+P:DaysF49 6.270e-02 7.216e-03 1.449e+03 8.689 < 2e-16
## TreatmentN:DaysF65 4.211e-02 7.173e-03 1.449e+03 5.871 5.36e-09
## TreatmentN+P:DaysF65 5.627e-02 7.241e-03 1.450e+03 7.770 1.47e-14
## TreatmentN:DaysF71 5.273e-02 7.248e-03 1.452e+03 7.276 5.63e-13
## TreatmentN+P:DaysF71 2.822e-02 7.241e-03 1.450e+03 3.897 0.000102
## TreatmentN:DaysF76 5.123e-02 7.275e-03 1.452e+03 7.041 2.93e-12
## TreatmentN+P:DaysF76 3.901e-02 7.241e-03 1.450e+03 5.387 8.33e-08
## TreatmentN:DaysF84 3.559e-02 7.801e-03 1.463e+03 4.562 5.48e-06
## TreatmentN+P:DaysF84 4.129e-02 7.733e-03 1.461e+03 5.339 1.08e-07
## TreatmentN:DaysF89 3.837e-02 7.847e-03 1.463e+03 4.890 1.12e-06
## TreatmentN+P:DaysF89 3.067e-02 7.733e-03 1.461e+03 3.966 7.67e-05
## TreatmentN:DaysF92 -5.437e-03 8.071e-03 1.465e+03 -0.674 0.500593
## TreatmentN+P:DaysF92 2.446e-02 7.863e-03 1.462e+03 3.110 0.001905
## TreatmentN:DaysF96 -4.797e-02 8.377e-03 1.467e+03 -5.727 1.24e-08
## TreatmentN+P:DaysF96 -1.997e-02 8.390e-03 1.466e+03 -2.380 0.017438
## TreatmentN:DaysF99 -1.156e-01 8.576e-03 1.468e+03 -13.482 < 2e-16
## TreatmentN+P:DaysF99 -4.191e-02 8.590e-03 1.467e+03 -4.879 1.18e-06
## TreatmentN:DaysF103 -1.112e-01 8.968e-03 1.469e+03 -12.400 < 2e-16
## TreatmentN+P:DaysF103 -9.820e-02 8.705e-03 1.467e+03 -11.280 < 2e-16
## TreatmentN:DaysF106 -1.810e-01 1.009e-02 1.473e+03 -17.929 < 2e-16
## TreatmentN+P:DaysF106 -1.426e-01 9.331e-03 1.470e+03 -15.285 < 2e-16
## TreatmentN+P:DaysF110 -1.302e-01 1.225e-02 1.476e+03 -10.630 < 2e-16
##
## (Intercept) ***
## TreatmentN *
## TreatmentN+P
## DaysF8
## DaysF14
## DaysF21
## DaysF28 *
## DaysF49 ***
## DaysF65 ***
## DaysF71 ***
## DaysF76 ***
## DaysF84 ***
## DaysF89 ***
## DaysF92 ***
## DaysF96 ***
## DaysF99 ***
## DaysF103 ***
## DaysF106 ***
## DaysF110 ***
## TreatmentN:DaysF8 ***
## TreatmentN+P:DaysF8 **
## TreatmentN:DaysF14
## TreatmentN+P:DaysF14 *
## TreatmentN:DaysF21 ***
## TreatmentN+P:DaysF21 ***
## TreatmentN:DaysF28 ***
## TreatmentN+P:DaysF28 ***
## TreatmentN:DaysF49 ***
## TreatmentN+P:DaysF49 ***
## TreatmentN:DaysF65 ***
## TreatmentN+P:DaysF65 ***
## TreatmentN:DaysF71 ***
## TreatmentN+P:DaysF71 ***
## TreatmentN:DaysF76 ***
## TreatmentN+P:DaysF76 ***
## TreatmentN:DaysF84 ***
## TreatmentN+P:DaysF84 ***
## TreatmentN:DaysF89 ***
## TreatmentN+P:DaysF89 ***
## TreatmentN:DaysF92
## TreatmentN+P:DaysF92 **
## TreatmentN:DaysF96 ***
## TreatmentN+P:DaysF96 *
## TreatmentN:DaysF99 ***
## TreatmentN+P:DaysF99 ***
## TreatmentN:DaysF103 ***
## TreatmentN+P:DaysF103 ***
## TreatmentN:DaysF106 ***
## TreatmentN+P:DaysF106 ***
## TreatmentN+P:DaysF110 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## fit warnings:
## fixed-effect model matrix is rank deficient so dropping 1 column / coefficient # EMMs
Acer.YII.emm<-emmeans(LME_Acer, ~Treatment * DaysF)
# contrast(Acer.YII.emm, "tukey")
# Effect plot options
emmip(LME_Acer, ~DaysF|Treatment, CIs = TRUE) + theme_bw() # interaction plot of predictions
# Pairwise comparisons
#pairs(Acer.YII.emm) # same than contrast(Acer.YII.emm, "tukey")
#plot(emmeans(LME_Acer, ~DaysF|Treatment), comparisons = TRUE) +
# coord_flip(xlim = NULL, ylim = NULL, expand = TRUE) + facet_wrap(~Treatment) +
# theme_gdocs() # Tukey comparission (do not trust CI to compare EMMs)
Acer.YII_groups<-cld(Acer.YII.emm, by=NULL) # compact-letter display
Acer.YII_groups<-Acer.YII_groups[order(Acer.YII_groups$Day,Acer.YII_groups$Treatment),]
Acer.YII_groups## Treatment DaysF emmean SE df lower.CL upper.CL
## 1 Ambient 1 0.6117575 0.007054394 10.280294 0.5960972 0.6274178
## 2 N 1 0.6005227 0.006988574 9.910625 0.5849322 0.6161133
## 3 N+P 1 0.6049142 0.007013858 10.056684 0.5892982 0.6205301
## 4 Ambient 8 0.6101165 0.007054394 10.280294 0.5944562 0.6257768
## 5 N 8 0.6263764 0.006988574 9.910625 0.6107858 0.6419670
## 6 N+P 8 0.6250892 0.007013858 10.056684 0.6094732 0.6407051
## 7 Ambient 14 0.6182190 0.007054394 10.280294 0.6025588 0.6338793
## 8 N 14 0.6151813 0.006988574 9.910625 0.5995907 0.6307718
## 9 N+P 14 0.6272392 0.007013858 10.056684 0.6116232 0.6428551
## 10 Ambient 21 0.6055267 0.007054394 10.280294 0.5898665 0.6211870
## 11 N 21 0.6386203 0.006988574 9.910625 0.6230297 0.6542109
## 12 N+P 21 0.6261892 0.007013858 10.056684 0.6105732 0.6418051
## 13 Ambient 28 0.6003216 0.007054394 10.280294 0.5846613 0.6159819
## 14 N 28 0.6308154 0.006988574 9.910625 0.6152248 0.6464060
## 15 N+P 28 0.6364392 0.007013858 10.056684 0.6208232 0.6520551
## 16 Ambient 49 0.5785524 0.007054394 10.280294 0.5628921 0.5942127
## 17 N 49 0.6348642 0.006988574 9.910625 0.6192736 0.6504548
## 18 N+P 49 0.6344142 0.007013858 10.056684 0.6187982 0.6500301
## 19 Ambient 65 0.5679883 0.007054394 10.280294 0.5523280 0.5836486
## 20 N 65 0.5988642 0.006988574 9.910625 0.5832736 0.6144548
## 21 N+P 65 0.6174144 0.007040543 10.209743 0.6017706 0.6330581
## 22 Ambient 71 0.5691934 0.007054394 10.280294 0.5535331 0.5848537
## 23 N 71 0.6106904 0.007067800 10.365157 0.5950172 0.6263636
## 24 N+P 71 0.5905682 0.007040543 10.209743 0.5749245 0.6062120
## 25 Ambient 76 0.5599370 0.007054394 10.280294 0.5442767 0.5755973
## 26 N 76 0.5999320 0.007097383 10.538342 0.5842269 0.6156371
## 27 N+P 76 0.5921067 0.007040543 10.209743 0.5764630 0.6077504
## 28 Ambient 84 0.5657458 0.007268878 11.587312 0.5498455 0.5816462
## 29 N 84 0.5900989 0.007429536 12.646142 0.5740026 0.6061952
## 30 N+P 84 0.6001896 0.007334650 12.022479 0.5842121 0.6161671
## 31 Ambient 89 0.5474646 0.007268878 11.587312 0.5315643 0.5633649
## 32 N 89 0.5745990 0.007478144 12.979606 0.5584408 0.5907571
## 33 N+P 89 0.5712896 0.007334650 12.022479 0.5553121 0.5872671
## 34 Ambient 92 0.5584958 0.007268878 11.587312 0.5425955 0.5743962
## 35 N 92 0.5418237 0.007719437 14.719734 0.5253427 0.5583046
## 36 N+P 92 0.5761104 0.007473578 12.954230 0.5599589 0.5922619
## 37 Ambient 96 0.5587146 0.007268878 11.587312 0.5428143 0.5746149
## 38 N 96 0.4995058 0.008038734 17.297257 0.4825678 0.5164439
## 39 N+P 96 0.5319028 0.008031063 17.245374 0.5149771 0.5488285
## 40 Ambient 99 0.5329958 0.007268878 11.587312 0.5170955 0.5488962
## 41 N 99 0.4061401 0.008247991 19.157904 0.3888865 0.4233937
## 42 N+P 99 0.4842428 0.008243048 19.121014 0.4669973 0.5014883
## 43 Ambient 103 0.5136521 0.007268878 11.587312 0.4977518 0.5295524
## 44 N 103 0.3912216 0.008656211 23.208304 0.3733238 0.4091195
## 45 N+P 103 0.4086126 0.008364655 20.266143 0.3911790 0.4260463
## 46 Ambient 106 0.4967458 0.007268878 11.587312 0.4808455 0.5126462
## 47 N 106 0.3045293 0.009818955 38.201452 0.2846553 0.3244033
## 48 N+P 106 0.3472829 0.009014907 27.273710 0.3287946 0.3657713
## 49 Ambient 110 0.3995271 0.007268878 11.587312 0.3836268 0.4154274
## 50 N 110 NA NA NA NA NA
## 51 N+P 110 0.2624893 0.012008996 83.678289 0.2386067 0.2863718
## .group
## 1 GHIJKL
## 2 EFGH
## 3 GHI
## 4 GHIJK
## 5 IJKLMN
## 6 IJKLMN
## 7 HIJKLMN
## 8 HIJKLM
## 9 JKLMN
## 10 GHIJ
## 11 N
## 12 JKLMN
## 13 FGH
## 14 KLMN
## 15 MN
## 16 0ABCDE
## 17 MN
## 18 LMN
## 19 890AB
## 20 EFGH
## 21 HIJKLMN
## 22 90ABC
## 23 GHIJK
## 24 BCDEFG
## 25 890
## 26 EFGH
## 27 CDEFG
## 28 890A
## 29 ABCDEFG
## 30 DEFGH
## 31 6789
## 32 0ABCD
## 33 90ABC
## 34 7890
## 35 678
## 36 0ABCDEF
## 37 7890
## 38 4
## 39 567
## 40 56
## 41 3
## 42 4
## 43 45
## 44 3
## 45 3
## 46 4
## 47 1
## 48 2
## 49 3
## 50
## 51 1 write.csv(Acer.YII_groups, "Outputs/Multicomp_AcerYII.csv", row.names = F)O.fav model
######
# Ofav
LME_Ofav<-lmer(YII ~ Treatment * DaysF + (1|Genotype/Fragment),
data=subset(YII.data, Spp=="O.fav"), na.action=na.omit)
lmerTest::step (LME_Ofav)## Backward reduced random-effect table:
##
## Eliminated npar logLik AIC LRT Df
## <none> 54 1915.5 -3722.9
## (1 | Fragment:Genotype) 0 53 1866.7 -3627.5 97.422 1
## (1 | Genotype) 0 53 1883.2 -3660.5 64.429 1
## Pr(>Chisq)
## <none>
## (1 | Fragment:Genotype) < 2.2e-16 ***
## (1 | Genotype) 1.001e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Backward reduced fixed-effect table:
## Degrees of freedom method: Satterthwaite
##
## Eliminated Sum Sq Mean Sq NumDF DenDF F value
## Treatment:DaysF 0 0.12191 0.0038097 32 867.62 5.2448
## Pr(>F)
## Treatment:DaysF < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Model found:
## YII ~ Treatment * DaysF + (1 | Genotype/Fragment) summary(LME_Ofav)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: YII ~ Treatment * DaysF + (1 | Genotype/Fragment)
## Data: subset(YII.data, Spp == "O.fav")
##
## REML criterion at convergence: -3830.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1623 -0.5974 0.0479 0.6430 2.4276
##
## Random effects:
## Groups Name Variance Std.Dev.
## Fragment:Genotype (Intercept) 0.0001798 0.01341
## Genotype (Intercept) 0.0006105 0.02471
## Residual 0.0007264 0.02695
## Number of obs: 983, groups: Fragment:Genotype, 72; Genotype, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.064e-01 1.380e-02 4.468e+00 36.702 1.03e-06
## TreatmentN 8.208e-03 8.690e-03 5.963e+02 0.945 0.345249
## TreatmentN+P 1.171e-02 8.690e-03 5.963e+02 1.347 0.178374
## DaysF8 -1.383e-02 7.780e-03 8.621e+02 -1.778 0.075756
## DaysF14 3.696e-02 7.780e-03 8.621e+02 4.750 2.38e-06
## DaysF21 -2.913e-02 7.780e-03 8.621e+02 -3.743 0.000194
## DaysF28 -1.375e-02 7.780e-03 8.621e+02 -1.767 0.077533
## DaysF49 -5.279e-02 7.780e-03 8.621e+02 -6.785 2.15e-11
## DaysF65 -5.500e-03 7.780e-03 8.621e+02 -0.707 0.479809
## DaysF71 -3.871e-02 7.780e-03 8.621e+02 -4.975 7.87e-07
## DaysF76 -3.904e-02 7.780e-03 8.621e+02 -5.018 6.34e-07
## DaysF84 -1.412e-02 8.765e-03 8.725e+02 -1.610 0.107671
## DaysF89 -2.868e-02 8.765e-03 8.725e+02 -3.272 0.001110
## DaysF92 9.563e-03 8.948e-03 8.735e+02 1.069 0.285445
## DaysF96 -7.277e-02 8.948e-03 8.735e+02 -8.133 1.43e-15
## DaysF99 -7.410e-02 8.948e-03 8.735e+02 -8.282 4.52e-16
## DaysF103 -9.450e-02 8.948e-03 8.735e+02 -10.562 < 2e-16
## DaysF106 -1.282e-01 9.149e-03 8.738e+02 -14.014 < 2e-16
## DaysF110 -9.172e-02 9.635e-03 8.739e+02 -9.519 < 2e-16
## TreatmentN:DaysF8 3.375e-03 1.100e-02 8.621e+02 0.307 0.759118
## TreatmentN+P:DaysF8 -4.417e-03 1.100e-02 8.621e+02 -0.401 0.688220
## TreatmentN:DaysF14 -1.654e-02 1.100e-02 8.621e+02 -1.503 0.133106
## TreatmentN+P:DaysF14 -5.542e-03 1.100e-02 8.621e+02 -0.504 0.614634
## TreatmentN:DaysF21 3.542e-03 1.100e-02 8.621e+02 0.322 0.747619
## TreatmentN+P:DaysF21 5.833e-03 1.100e-02 8.621e+02 0.530 0.596137
## TreatmentN:DaysF28 1.900e-02 1.100e-02 8.621e+02 1.727 0.084560
## TreatmentN+P:DaysF28 3.329e-02 1.100e-02 8.621e+02 3.026 0.002554
## TreatmentN:DaysF49 3.117e-02 1.100e-02 8.621e+02 2.833 0.004725
## TreatmentN+P:DaysF49 3.867e-02 1.100e-02 8.621e+02 3.514 0.000464
## TreatmentN:DaysF65 -2.871e-02 1.100e-02 8.621e+02 -2.609 0.009234
## TreatmentN+P:DaysF65 1.417e-03 1.100e-02 8.621e+02 0.129 0.897583
## TreatmentN:DaysF71 -1.083e-03 1.100e-02 8.621e+02 -0.098 0.921591
## TreatmentN+P:DaysF71 -3.308e-02 1.100e-02 8.621e+02 -3.007 0.002717
## TreatmentN:DaysF76 -2.708e-03 1.100e-02 8.621e+02 -0.246 0.805628
## TreatmentN+P:DaysF76 -9.458e-03 1.100e-02 8.621e+02 -0.860 0.390239
## TreatmentN:DaysF84 -7.511e-03 1.240e-02 8.725e+02 -0.606 0.544693
## TreatmentN+P:DaysF84 1.463e-03 1.240e-02 8.725e+02 0.118 0.906102
## TreatmentN:DaysF89 -2.342e-02 1.253e-02 8.731e+02 -1.870 0.061807
## TreatmentN+P:DaysF89 6.501e-04 1.240e-02 8.725e+02 0.052 0.958188
## TreatmentN:DaysF92 -2.684e-02 1.280e-02 8.742e+02 -2.097 0.036282
## TreatmentN+P:DaysF92 -3.208e-02 1.265e-02 8.735e+02 -2.535 0.011421
## TreatmentN:DaysF96 -4.006e-03 1.280e-02 8.742e+02 -0.313 0.754359
## TreatmentN+P:DaysF96 6.940e-03 1.280e-02 8.740e+02 0.542 0.587749
## TreatmentN:DaysF99 -3.117e-02 1.280e-02 8.742e+02 -2.436 0.015068
## TreatmentN+P:DaysF99 -6.276e-03 1.337e-02 8.750e+02 -0.469 0.638922
## TreatmentN:DaysF103 -2.270e-02 1.280e-02 8.742e+02 -1.774 0.076466
## TreatmentN+P:DaysF103 4.487e-03 1.337e-02 8.750e+02 0.336 0.737273
## TreatmentN:DaysF106 -3.712e-02 1.310e-02 8.746e+02 -2.833 0.004710
## TreatmentN+P:DaysF106 -2.553e-02 1.351e-02 8.753e+02 -1.890 0.059045
## TreatmentN:DaysF110 -7.150e-02 1.362e-02 8.753e+02 -5.248 1.93e-07
## TreatmentN+P:DaysF110 -3.448e-02 1.384e-02 8.759e+02 -2.492 0.012890
##
## (Intercept) ***
## TreatmentN
## TreatmentN+P
## DaysF8 .
## DaysF14 ***
## DaysF21 ***
## DaysF28 .
## DaysF49 ***
## DaysF65
## DaysF71 ***
## DaysF76 ***
## DaysF84
## DaysF89 **
## DaysF92
## DaysF96 ***
## DaysF99 ***
## DaysF103 ***
## DaysF106 ***
## DaysF110 ***
## TreatmentN:DaysF8
## TreatmentN+P:DaysF8
## TreatmentN:DaysF14
## TreatmentN+P:DaysF14
## TreatmentN:DaysF21
## TreatmentN+P:DaysF21
## TreatmentN:DaysF28 .
## TreatmentN+P:DaysF28 **
## TreatmentN:DaysF49 **
## TreatmentN+P:DaysF49 ***
## TreatmentN:DaysF65 **
## TreatmentN+P:DaysF65
## TreatmentN:DaysF71
## TreatmentN+P:DaysF71 **
## TreatmentN:DaysF76
## TreatmentN+P:DaysF76
## TreatmentN:DaysF84
## TreatmentN+P:DaysF84
## TreatmentN:DaysF89 .
## TreatmentN+P:DaysF89
## TreatmentN:DaysF92 *
## TreatmentN+P:DaysF92 *
## TreatmentN:DaysF96
## TreatmentN+P:DaysF96
## TreatmentN:DaysF99 *
## TreatmentN+P:DaysF99
## TreatmentN:DaysF103 .
## TreatmentN+P:DaysF103
## TreatmentN:DaysF106 **
## TreatmentN+P:DaysF106 .
## TreatmentN:DaysF110 ***
## TreatmentN+P:DaysF110 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 # EMMs
Ofav.YII.emm<-emmeans(LME_Ofav, ~Treatment * DaysF)
# contrast(Ofav.YII.emm, "tukey")
# Effect plot options
emmip(LME_Ofav, ~DaysF|Treatment, CIs = TRUE) + theme_gdocs() # interaction plot of predictions
# Pairwise comparisons
#pairs(Ofav.YII.emm) # same than contrast(Acer.YII.emm, "tukey")
# Pairwise comparisons
plot(emmeans(LME_Ofav, ~DaysF|Treatment), comparisons = TRUE) +
coord_flip(xlim = NULL, ylim = NULL, expand = TRUE) +
facet_wrap(~Treatment) +
theme_bw() # Tukey comparission (do not trust CI to compare EMMs)
Ofav.YII_groups<-cld(Ofav.YII.emm, by=NULL) # compact-letter display
Ofav.YII_groups<-Ofav.YII_groups[order(Ofav.YII_groups$Day,Ofav.YII_groups$Treatment),]
Ofav.YII_groups## Treatment DaysF emmean SE df lower.CL upper.CL
## 1 Ambient 1 0.5064167 0.01379815 4.471946 0.4696499 0.5431835
## 2 N 1 0.5146250 0.01379815 4.471946 0.4778582 0.5513918
## 3 N+P 1 0.5181250 0.01379815 4.471946 0.4813582 0.5548918
## 4 Ambient 8 0.4925833 0.01379815 4.471946 0.4558165 0.5293501
## 5 N 8 0.5041667 0.01379815 4.471946 0.4673999 0.5409335
## 6 N+P 8 0.4998750 0.01379815 4.471946 0.4631082 0.5366418
## 7 Ambient 14 0.5433750 0.01379815 4.471946 0.5066082 0.5801418
## 8 N 14 0.5350417 0.01379815 4.471946 0.4982749 0.5718085
## 9 N+P 14 0.5495417 0.01379815 4.471946 0.5127749 0.5863085
## 10 Ambient 21 0.4772917 0.01379815 4.471946 0.4405249 0.5140585
## 11 N 21 0.4890417 0.01379815 4.471946 0.4522749 0.5258085
## 12 N+P 21 0.4948333 0.01379815 4.471946 0.4580665 0.5316001
## 13 Ambient 28 0.4926667 0.01379815 4.471946 0.4558999 0.5294335
## 14 N 28 0.5198750 0.01379815 4.471946 0.4831082 0.5566418
## 15 N+P 28 0.5376667 0.01379815 4.471946 0.5008999 0.5744335
## 16 Ambient 49 0.4536250 0.01379815 4.471946 0.4168582 0.4903918
## 17 N 49 0.4930000 0.01379815 4.471946 0.4562332 0.5297668
## 18 N+P 49 0.5040000 0.01379815 4.471946 0.4672332 0.5407668
## 19 Ambient 65 0.5009167 0.01379815 4.471946 0.4641499 0.5376835
## 20 N 65 0.4804167 0.01379815 4.471946 0.4436499 0.5171835
## 21 N+P 65 0.5140417 0.01379815 4.471946 0.4772749 0.5508085
## 22 Ambient 71 0.4677083 0.01379815 4.471946 0.4309415 0.5044751
## 23 N 71 0.4748333 0.01379815 4.471946 0.4380665 0.5116001
## 24 N+P 71 0.4463333 0.01379815 4.471946 0.4095665 0.4831001
## 25 Ambient 76 0.4673750 0.01379815 4.471946 0.4306082 0.5041418
## 26 N 76 0.4728750 0.01379815 4.471946 0.4361082 0.5096418
## 27 N+P 76 0.4696250 0.01379815 4.471946 0.4328582 0.5063918
## 28 Ambient 84 0.4923014 0.01437743 5.269204 0.4559038 0.5286990
## 29 N 84 0.4929983 0.01437743 5.269204 0.4566008 0.5293959
## 30 N+P 84 0.5054723 0.01437743 5.269204 0.4690747 0.5418699
## 31 Ambient 89 0.4777389 0.01437743 5.269204 0.4413413 0.5141365
## 32 N 89 0.4625228 0.01449003 5.435763 0.4261554 0.4988901
## 33 N+P 89 0.4900973 0.01437743 5.269204 0.4536997 0.5264949
## 34 Ambient 92 0.5159799 0.01448951 5.434999 0.4796125 0.5523473
## 35 N 92 0.4973489 0.01461734 5.628795 0.4610019 0.5336959
## 36 N+P 92 0.4956130 0.01448951 5.434999 0.4592456 0.5319805
## 37 Ambient 96 0.4336466 0.01448951 5.434999 0.3972792 0.4700140
## 38 N 96 0.4378489 0.01461734 5.628795 0.4015019 0.4741959
## 39 N+P 96 0.4522952 0.01461626 5.627189 0.4159482 0.4886422
## 40 Ambient 99 0.4323132 0.01448951 5.434999 0.3959458 0.4686807
## 41 N 99 0.4093489 0.01461734 5.628795 0.3730019 0.4456959
## 42 N+P 99 0.4377452 0.01512243 6.445708 0.4013534 0.4741370
## 43 Ambient 103 0.4119132 0.01448951 5.434999 0.3755458 0.4482807
## 44 N 103 0.3974203 0.01461734 5.628795 0.3610733 0.4337673
## 45 N+P 103 0.4281088 0.01512243 6.445708 0.3917171 0.4645006
## 46 Ambient 106 0.3782053 0.01461499 5.625295 0.3418582 0.4145523
## 47 N 106 0.3492897 0.01476106 5.852906 0.3129495 0.3856298
## 48 N+P 106 0.3643816 0.01512243 6.445708 0.3279898 0.4007734
## 49 Ambient 110 0.4147013 0.01492391 6.115019 0.3783497 0.4510530
## 50 N 110 0.3514105 0.01492677 6.119543 0.3150583 0.3877628
## 51 N+P 110 0.3919270 0.01512243 6.445708 0.3555352 0.4283188
## .group
## 1 FGHIJKL
## 2 IJKLMN
## 3 JKLM
## 4 BCDEFGHIJ
## 5 E GHIJKL
## 6 BCDEFGHIJ
## 7 MN
## 8 KLMN
## 9 N
## 10 890ABCDEFG
## 11 ABCDEFGHIJ
## 12 BCDEFGHIJ
## 13 BCDEFGHIJ
## 14 JKLMN
## 15 LMN
## 16 67890
## 17 BCDEFGHIJ
## 18 FGHIJK
## 19 C EFGHIJK
## 20 90ABCDEFGH
## 21 HIJKLM
## 22 67890AB D
## 23 90ABCDEFG
## 24 56789
## 25 67890AB D
## 26 890ABCD F
## 27 7890ABC E
## 28 ABCDEFGHIJ
## 29 ABCDEFGHIJ
## 30 D FGHIJKLM
## 31 890ABCDEFGHI
## 32 67890ABC
## 33 0ABCDEFGHIJ
## 34 HIJKLMN
## 35 BCDEFGHIJ
## 36 BCDEFGHIJ
## 37 4567
## 38 45678
## 39 567890A
## 40 4567
## 41 2345
## 42 456789
## 43 345
## 44 234
## 45 456
## 46 123
## 47 1
## 48 12
## 49 345
## 50 1
## 51 1234 write.csv(Ofav.YII_groups, "Outputs/Multicomp_OfavYII.csv", row.names = F)Ssid model
LME_Ssid<-lmer(YII ~ Treatment * DaysF + (1|Genotype/Fragment),
REML=TRUE, data=subset(YII.data, Spp=="S.sid"),
na.action=na.omit)
step (LME_Ssid)## Backward reduced random-effect table:
##
## Eliminated npar logLik AIC LRT Df
## <none> 54 3774.8 -7441.7
## (1 | Fragment:Genotype) 0 53 3759.5 -7412.9 30.718 1
## (1 | Genotype) 0 53 3730.7 -7355.5 88.185 1
## Pr(>Chisq)
## <none>
## (1 | Fragment:Genotype) 2.983e-08 ***
## (1 | Genotype) < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Backward reduced fixed-effect table:
## Degrees of freedom method: Satterthwaite
##
## Eliminated Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## Treatment:DaysF 0 0.39611 0.012379 32 2205.3 5.8963 < 2.2e-16
##
## Treatment:DaysF ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Model found:
## YII ~ Treatment * DaysF + (1 | Genotype/Fragment) summary(LME_Ssid)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: YII ~ Treatment * DaysF + (1 | Genotype/Fragment)
## Data: subset(YII.data, Spp == "S.sid")
##
## REML criterion at convergence: -7549.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -6.3946 -0.4867 0.0610 0.6196 2.6395
##
## Random effects:
## Groups Name Variance Std.Dev.
## Fragment:Genotype (Intercept) 0.0001237 0.01112
## Genotype (Intercept) 0.0003108 0.01763
## Residual 0.0020994 0.04582
## Number of obs: 2414, groups: Fragment:Genotype, 162; Genotype, 7
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.668e-01 9.250e-03 2.069e+01 50.458 < 2e-16
## TreatmentN -2.529e-02 9.033e-03 2.231e+03 -2.800 0.005157
## TreatmentN+P -7.407e-03 9.117e-03 2.231e+03 -0.812 0.416604
## DaysF8 2.765e-02 8.818e-03 2.194e+03 3.135 0.001738
## DaysF14 8.424e-02 8.818e-03 2.194e+03 9.553 < 2e-16
## DaysF21 2.272e-02 8.818e-03 2.194e+03 2.577 0.010035
## DaysF28 6.363e-02 8.818e-03 2.194e+03 7.216 7.34e-13
## DaysF49 2.057e-02 8.818e-03 2.194e+03 2.333 0.019726
## DaysF65 2.521e-02 8.861e-03 2.196e+03 2.845 0.004483
## DaysF71 1.457e-02 8.861e-03 2.197e+03 1.645 0.100184
## DaysF76 1.538e-02 8.861e-03 2.197e+03 1.736 0.082666
## DaysF84 2.149e-03 9.659e-03 2.234e+03 0.222 0.823973
## DaysF89 -2.731e-02 9.659e-03 2.234e+03 -2.828 0.004728
## DaysF92 -1.844e-02 9.659e-03 2.234e+03 -1.909 0.056352
## DaysF96 -9.124e-02 9.659e-03 2.234e+03 -9.446 < 2e-16
## DaysF99 -9.139e-02 9.659e-03 2.234e+03 -9.462 < 2e-16
## DaysF103 -1.135e-01 9.659e-03 2.234e+03 -11.756 < 2e-16
## DaysF106 -1.247e-01 9.659e-03 2.234e+03 -12.908 < 2e-16
## DaysF110 -9.567e-02 9.659e-03 2.234e+03 -9.905 < 2e-16
## TreatmentN:DaysF8 2.890e-02 1.241e-02 2.194e+03 2.328 0.020008
## TreatmentN+P:DaysF8 3.954e-02 1.253e-02 2.194e+03 3.156 0.001622
## TreatmentN:DaysF14 2.145e-02 1.241e-02 2.194e+03 1.728 0.084134
## TreatmentN+P:DaysF14 1.157e-02 1.253e-02 2.194e+03 0.924 0.355846
## TreatmentN:DaysF21 4.150e-02 1.241e-02 2.194e+03 3.343 0.000843
## TreatmentN+P:DaysF21 4.147e-02 1.253e-02 2.194e+03 3.310 0.000949
## TreatmentN:DaysF28 4.619e-02 1.241e-02 2.194e+03 3.721 0.000204
## TreatmentN+P:DaysF28 2.580e-02 1.253e-02 2.194e+03 2.060 0.039557
## TreatmentN:DaysF49 2.690e-02 1.241e-02 2.194e+03 2.167 0.030351
## TreatmentN+P:DaysF49 6.143e-03 1.253e-02 2.194e+03 0.490 0.623974
## TreatmentN:DaysF65 -2.066e-02 1.244e-02 2.195e+03 -1.660 0.096961
## TreatmentN+P:DaysF65 -2.271e-03 1.259e-02 2.196e+03 -0.180 0.856865
## TreatmentN:DaysF71 4.335e-03 1.244e-02 2.196e+03 0.348 0.727577
## TreatmentN+P:DaysF71 8.038e-04 1.256e-02 2.196e+03 0.064 0.948976
## TreatmentN:DaysF76 5.597e-03 1.244e-02 2.196e+03 0.450 0.652928
## TreatmentN+P:DaysF76 -2.234e-03 1.256e-02 2.196e+03 -0.178 0.858843
## TreatmentN:DaysF84 -1.148e-02 1.353e-02 2.232e+03 -0.848 0.396344
## TreatmentN+P:DaysF84 7.540e-03 1.363e-02 2.231e+03 0.553 0.580292
## TreatmentN:DaysF89 1.142e-02 1.353e-02 2.232e+03 0.844 0.398890
## TreatmentN+P:DaysF89 -8.473e-03 1.363e-02 2.231e+03 -0.622 0.534332
## TreatmentN:DaysF92 2.667e-02 1.353e-02 2.232e+03 1.971 0.048895
## TreatmentN+P:DaysF92 6.155e-03 1.363e-02 2.231e+03 0.451 0.651720
## TreatmentN:DaysF96 6.744e-02 1.353e-02 2.232e+03 4.983 6.74e-07
## TreatmentN+P:DaysF96 2.480e-02 1.363e-02 2.231e+03 1.819 0.069048
## TreatmentN:DaysF99 5.942e-02 1.353e-02 2.232e+03 4.391 1.18e-05
## TreatmentN+P:DaysF99 1.053e-02 1.363e-02 2.231e+03 0.772 0.440057
## TreatmentN:DaysF103 7.831e-02 1.353e-02 2.232e+03 5.786 8.22e-09
## TreatmentN+P:DaysF103 2.183e-02 1.363e-02 2.231e+03 1.601 0.109443
## TreatmentN:DaysF106 5.500e-02 1.353e-02 2.232e+03 4.064 5.00e-05
## TreatmentN+P:DaysF106 7.411e-03 1.363e-02 2.231e+03 0.544 0.586811
## TreatmentN:DaysF110 6.507e-02 1.353e-02 2.232e+03 4.808 1.63e-06
## TreatmentN+P:DaysF110 1.869e-02 1.363e-02 2.231e+03 1.371 0.170659
##
## (Intercept) ***
## TreatmentN **
## TreatmentN+P
## DaysF8 **
## DaysF14 ***
## DaysF21 *
## DaysF28 ***
## DaysF49 *
## DaysF65 **
## DaysF71
## DaysF76 .
## DaysF84
## DaysF89 **
## DaysF92 .
## DaysF96 ***
## DaysF99 ***
## DaysF103 ***
## DaysF106 ***
## DaysF110 ***
## TreatmentN:DaysF8 *
## TreatmentN+P:DaysF8 **
## TreatmentN:DaysF14 .
## TreatmentN+P:DaysF14
## TreatmentN:DaysF21 ***
## TreatmentN+P:DaysF21 ***
## TreatmentN:DaysF28 ***
## TreatmentN+P:DaysF28 *
## TreatmentN:DaysF49 *
## TreatmentN+P:DaysF49
## TreatmentN:DaysF65 .
## TreatmentN+P:DaysF65
## TreatmentN:DaysF71
## TreatmentN+P:DaysF71
## TreatmentN:DaysF76
## TreatmentN+P:DaysF76
## TreatmentN:DaysF84
## TreatmentN+P:DaysF84
## TreatmentN:DaysF89
## TreatmentN+P:DaysF89
## TreatmentN:DaysF92 *
## TreatmentN+P:DaysF92
## TreatmentN:DaysF96 ***
## TreatmentN+P:DaysF96 .
## TreatmentN:DaysF99 ***
## TreatmentN+P:DaysF99
## TreatmentN:DaysF103 ***
## TreatmentN+P:DaysF103
## TreatmentN:DaysF106 ***
## TreatmentN+P:DaysF106
## TreatmentN:DaysF110 ***
## TreatmentN+P:DaysF110
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 # EMMs
Ssid.YII.emm<-emmeans(LME_Ssid, ~Treatment * DaysF)
# contrast(Ssid.YII.emm, "tukey")
# Effect plot options
emmip(LME_Ssid, ~DaysF|Treatment, CIs = TRUE) + theme_gdocs() # interaction plot of predictions
# Pairwise comparisons
# pairs(Ssid.YII.emm) # same than contrast(Ssid.YII.emm, "tukey")
# Tukey comparission (do not trust CI to compare EMMs)
plot(emmeans(LME_Ssid, ~DaysF|Treatment), comparisons = TRUE) +
coord_flip(xlim = NULL, ylim = NULL, expand = TRUE) + facet_wrap(~Treatment) +
theme_gdocs()
Ssid.YII_groups<-cld(Ssid.YII.emm, by=NULL) # compact-letter display
Ssid.YII_groups<-Ssid.YII_groups[order(Ssid.YII_groups$Day,Ssid.YII_groups$Treatment),]
Ssid.YII_groups## Treatment DaysF emmean SE df lower.CL upper.CL
## 1 Ambient 1 0.4667566 0.009250378 20.66614 0.4475004 0.4860127
## 2 N 1 0.4414666 0.009209706 20.30662 0.4222741 0.4606591
## 3 N+P 1 0.4593494 0.009292842 21.04607 0.4400264 0.4786723
## 4 Ambient 8 0.4944047 0.009250378 20.66614 0.4751485 0.5136609
## 5 N 8 0.4980121 0.009209706 20.30662 0.4788195 0.5172046
## 6 N+P 8 0.5265381 0.009292842 21.04607 0.5072151 0.5458610
## 7 Ambient 14 0.5509973 0.009250378 20.66614 0.5317411 0.5702534
## 8 N 14 0.5471575 0.009209706 20.30662 0.5279650 0.5663501
## 9 N+P 14 0.5551607 0.009292842 21.04607 0.5358378 0.5744837
## 10 Ambient 21 0.4894788 0.009250378 20.66614 0.4702226 0.5087349
## 11 N 21 0.5056848 0.009209706 20.30662 0.4864923 0.5248773
## 12 N+P 21 0.5235381 0.009292842 21.04607 0.5042151 0.5428610
## 13 Ambient 28 0.5303862 0.009250378 20.66614 0.5111300 0.5496423
## 14 N 28 0.5512848 0.009209706 20.30662 0.5320923 0.5704773
## 15 N+P 28 0.5487834 0.009292842 21.04607 0.5294604 0.5681063
## 16 Ambient 49 0.4873306 0.009250378 20.66614 0.4680745 0.5065868
## 17 N 49 0.4889393 0.009209706 20.30662 0.4697468 0.5081319
## 18 N+P 49 0.4860664 0.009292842 21.04607 0.4667434 0.5053893
## 19 Ambient 65 0.4919649 0.009291166 21.03123 0.4726446 0.5112852
## 20 N 65 0.4460121 0.009209706 20.30662 0.4268195 0.4652046
## 21 N+P 65 0.4822866 0.009334978 21.42846 0.4628970 0.5016761
## 22 Ambient 71 0.4813301 0.009291639 21.03540 0.4620091 0.5006511
## 23 N 71 0.4603757 0.009209706 20.30662 0.4411832 0.4795682
## 24 N+P 71 0.4747267 0.009292842 21.04607 0.4554038 0.4940497
## 25 Ambient 76 0.4821414 0.009291639 21.03540 0.4628204 0.5014625
## 26 N 76 0.4624484 0.009209706 20.30662 0.4432559 0.4816410
## 27 N+P 76 0.4725003 0.009292842 21.04607 0.4531774 0.4918233
## 28 Ambient 84 0.4689052 0.010055888 28.80008 0.4483324 0.4894780
## 29 N 84 0.4321341 0.009918204 27.26565 0.4117929 0.4524753
## 30 N+P 84 0.4690381 0.009986807 28.02280 0.4485818 0.4894944
## 31 Ambient 89 0.4394437 0.010055888 28.80008 0.4188709 0.4600165
## 32 N 89 0.4255732 0.009918204 27.26565 0.4052320 0.4459144
## 33 N+P 89 0.4235631 0.009986807 28.02280 0.4031068 0.4440194
## 34 Ambient 92 0.4483155 0.010055888 28.80008 0.4277427 0.4688883
## 35 N 92 0.4496951 0.009918204 27.26565 0.4293539 0.4700363
## 36 N+P 92 0.4470631 0.009986807 28.02280 0.4266068 0.4675194
## 37 Ambient 96 0.3755206 0.010055888 28.80008 0.3549478 0.3960934
## 38 N 96 0.4176707 0.009918204 27.26565 0.3973295 0.4380119
## 39 N+P 96 0.3929131 0.009986807 28.02280 0.3724568 0.4133694
## 40 Ambient 99 0.3753668 0.010055888 28.80008 0.3547940 0.3959396
## 41 N 99 0.4095000 0.009918204 27.26565 0.3891588 0.4298412
## 42 N+P 99 0.3784881 0.009986807 28.02280 0.3580318 0.3989444
## 43 Ambient 103 0.3532129 0.010055888 28.80008 0.3326401 0.3737857
## 44 N 103 0.4062317 0.009918204 27.26565 0.3858905 0.4265729
## 45 N+P 103 0.3676381 0.009986807 28.02280 0.3471818 0.3880944
## 46 Ambient 106 0.3420847 0.010055888 28.80008 0.3215119 0.3626575
## 47 N 106 0.3717927 0.009918204 27.26565 0.3514515 0.3921339
## 48 N+P 106 0.3420881 0.009986807 28.02280 0.3216318 0.3625444
## 49 Ambient 110 0.3710847 0.010055888 28.80008 0.3505119 0.3916575
## 50 N 110 0.4108658 0.009918204 27.26565 0.3905246 0.4312070
## 51 N+P 110 0.3823631 0.009986807 28.02280 0.3619068 0.4028194
## .group
## 1 0ABCDEF
## 2 7890A
## 3 90ABCDE
## 4 EFGHI
## 5 FGHIJ
## 6 IJK
## 7 K
## 8 K
## 9 K
## 10 EFGH
## 11 GHIJ
## 12 HIJK
## 13 JK
## 14 K
## 15 K
## 16 DEFGH
## 17 EFGH
## 18 CDEFG
## 19 EFGHI
## 20 890AB
## 21 BCDEFG
## 22 BCDEFG
## 23 90ABCDE
## 24 ABCDEFG
## 25 BCDEFG
## 26 90ABCDE
## 27 ABCDEFG
## 28 0ABCDEFG
## 29 67890
## 30 0ABCDEFG
## 31 7890A
## 32 6789
## 33 6789
## 34 7890ABC
## 35 890ABCD
## 36 7890AB
## 37 12345
## 38 5678
## 39 23456
## 40 1234
## 41 345678
## 42 12345
## 43 12
## 44 34567
## 45 123
## 46 1
## 47 1234
## 48 1
## 49 1234
## 50 45678
## 51 12345 write.csv(Ssid.YII_groups, "Outputs/Multicomp_SsidYII.csv", row.names = F)Only nutrients
############################################################
################### ONLY NUTRIENT PHASE ##################
############################################################
# Select data for Nutrient enrichment (26C) only
# Raw YII data
YII_Colony<- ggplot(YII.nutrients, aes (Days, YII, colour=Genotype)) +
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar", width = 0.2 )+
stat_summary(fun.y=mean, geom="line") + theme_gdocs()
YII_Colony + ylim(0.0, 0.65) + facet_grid (Spp~Treatment)
YII_Fragm<- ggplot(YII.nutrients, aes (Days, YII, colour=Treatment)) +
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar", width = 0.2 )+
stat_summary(fun.y=mean, geom="line") + ggthe_bw
YII_Fragm + ylim(0.25, 0.65) + facet_wrap (Spp~Genotype)
YII_Trea<- ggplot(YII.nutrients, aes (Days, YII, colour=factor(Treatment))) +
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar",
position = position_dodge(width = 1), width = 0.2 )+
stat_summary(fun.y=mean, geom="line") +
facet_grid (~Spp) + theme_gdocs()+
scale_x_continuous(name="Days in nutrient treatment",
breaks=c(seq(-30,76, by=15))) +
ylab("Fv/Fm") + ylim(0.01, 0.65)
YII_Trea + guides(colour=guide_legend("Treatment"))+
theme(legend.position=c(0.15, 0.3),
plot.background=element_blank(),
legend.box.background = element_rect())